Monitoring electrical muscular activity

ABSTRACT

A method of monitoring electrical activity non-invasively (such as uterine activity) which includes applying a localized group of electrodes to a patient&#39;s skin and monitoring signals thereon. The electrodes are localized sufficiently such that their muscular signal contributions simulate a single source despite source non-stationarity. The signals are amplified, filtered and digitized. They are then digitally filtered and processed by independent component analysis (ICA) to separate a muscular activity source from other sources. The method may be used to monitor maternal uterine activity, fetal activity and maternal and fetal cardiac activity simultaneously with the aid of additional electrodes and associated circuitry.

This invention relates to a method of and apparatus for monitoringelectrical muscular activity non-invasively. It is particularly(although not exclusively) relevant to monitoring uterine contractionsduring pregnancy and labour.

Myometrial activity varies throughout pregnancy and labour. Themyometrium—the muscular region of the uterus—is never completelyrelaxed, and from early gestation it contracts at regular intervals;these contractions are painless and are known as Braxton HicksContractions. Up until the end of pregnancy's second trimester, uterineactivity is restricted to small, localised contractions, approximatelyevery minute, with larger contractions every 30 to 60 minutes. Theselarger contractions increase with frequency and intensity throughout thethird trimester until the onset of labour. The onset of labour is asubjective assessment based on the frequency of painful contractions andthe progressive dilation of the cervix. Preterm labour remains theleading cause of neonatal mortality and morbidity. The current EPIcurestudy by Costeloe K, Gibson A T, Marlow N, Wilkinson A R, is looking at,‘The outcome to discharge from hospital for babies born at the thresholdof viability’. This suggests that almost 50% of babies born in the UK at23-25 weeks gestation will have significant long-term handicap.Throughout normal labour the intensity, frequency, and duration ofcontractions increases to 2-4 contractions every 10 minutes withprogressive lengthening from 20 seconds in early labour to 40-90 secondsby the end of the first stage of labour. It is described by LlewelynJones in, ‘Fundamentals of Obstetrics and Gynaecology’. It, is thereforehighly desirable to monitor myometrial activity routinely to provideadvance warning of premature labour.

Existing methods of monitoring uterine contractions are subjective andprincipally rely on the frequency of contractions alone to predict onsetof labour. Throughout pregnancy this generally relies on symptomaticself-monitoring which lacks accuracy, especially in first pregnancies.During the third trimester a tocodynamometer may be used, this being apressure transducer which monitors the pressure that the uterus exertson the abdominal wall. It is strapped around the abdomen and indicatesthe frequency of contractions and subjectively measures contractionmagnitude, which is sensitive to the pressure with which and position towhich the transducer is applied.

An intrauterine pressure monitor is a known accurate tool fordetermining uterine pressure. It is designed to detect and measureintrauterine and amniotic fluid pressure with a catheter placedtranscervically into the uterine cavity. It is used to monitorintensity, duration, and frequency of uterine contractions. Despite itsaccuracy in monitoring the above parameters it involves a bodilyinvasive procedure and is generally only used in clinical environments.If a reliable non-invasive technique were available then this would bereadily accepted by clinicians.

The uterine electromyogram (EMG), or electrohysterogram (EHG), wasdiscovered in 1849. Technical difficulties in obtaining reliablenon-invasive EHG measurements, despite many years of research, has ledto this being far less commonplace than other electrophysiologicalmonitoring techniques. Many studies have previously recorded the EHGthrough invasive means and attempted to understand the mechanism ofcontractile activity, Garfield et al., “Control of MyometrialContractility: Role and Regulation of Gap Junctions,” Oxford Rev.Reprod. Biol. 10:436-490, 1988; Devedeux D, Marque C, Mansour S, GermainG, Duchene J, 1992, Uterine, electromyography: a critical review,American Journal of Obstetrics and Gynecology, VOL. 169, No. 6 pp1636-1653.

A number of studies have shown that non-invasive trans-abdominalrecordings of the EHG are possible using signal acquisition equipmentcentered around a differential pair of electrodes, although theyacknowledge that signal denoising and removal of unwanted biologicalartefacts is necessary for successful interpretation. These studiesinclude Simpson N. A. B. et al, 1998 ‘Changes in uterine electricalactivity associated with onset of labour in human pregnancy’, Journal ofphysiology 507.P, 68P; Lenman H, Marque C, ‘Rejection of the MaternalElectrocardiogram in the Electrohysterogram Signal’, 2000, IEEETransactions on Biomed. Eng. Vol. 47, No. 8.

To improve reliability of extracting the uterine EMG and to allow itsaccurate classification, more recent investigations relate to de-noisingthe contractile wave and characterising the contractions duringpregnancy to allow prediction of pre-term labour. See Carre P, Lenman H,Fernandez C, Marque C, 1998, ‘Denoising of the Uterine EHG by anUndecimated Wavelet Transform’, IEEE Transactions on Biomed. Eng. Vol.45, No. 9; Khalil M, 2000, Uterine EMG Analysis: A Dynamic Approach forChange Detection and Classification, IEEE Transactions on Biomed. Eng.Vol. 47, No. 6.

Further studies have concentrated on the diagnosis of labour based onthe uterine EMG, see Rosenberg E, 1996, U.S. Pat. No. 5,483,970,‘Apparatus and Methods for the Diagnosis of Labour’. This referencelooks at the uterine EMG across a patient's abdomen. It uses a techniquethat forms an envelope around the contractile wave to monitorprogression of a contraction across the abdomen whilst compensating forany conduction abnormalities. The information obtained is then combinedwith a direct current offset technique to determine cervical dilation.This apparatus relies on specific placement of electrodes and selectionof various coordinate systems for the technique to be successful. Theapparatus concentrates on monitoring the progression of labour ratherthan fetal well-being, although the two can be indirectly related.

There are few investigations suggesting the combination of non-invasiveuterine EMG with non-invasive fetal electrocardiography (fECG) foreither antenatal screening and monitoring in addition to a tool formonitoring labour events and fetal well-being. Published InternationalPatent Application No. WO 02/096288 (hereinafter “WO/288”) suggests anapparatus for the detection and analysis of maternal uterine, maternaland fetal cardiac and fetal brain activity although it is unclear whichtechnique is used to extract which signals and what method in particularis used to extract the fetal electrocardiogram. It refers to (presumablyfetal) scalp electrodes for fetal brain activity, and to transcervicaland transvaginal as well as transabdominal recordings which indicates itis not completely non-invasive. It suggests that cardiac QRST tracingsare obtainable via Doppler ultrasound and pulse oximetry and/or othermethods. It also suggests recording transabdominal electrical signals,although the suggested frequency bands of interest for fECG, 1-5 Hz and20-200 Hz, are not the expected range of 0.5-150 Hz. This range wasfound during a study associated with International Patent ApplicationNo. GB2002/004410 (hereinafter “GB4410”) involving over six hundredpatients, and is suggested by the American Heart Association Standardsfor Electrocardiography. However no current standards apply specificallyto fECG because of the inability to measure it sufficiently accuratelyprior to GB4410. In WO/288 the amplitude of cardiac action potentials isstated as 110-140 mV: abdominal electrodes with a 2KΩ electrode skinimpedance tend to detect a maternal signal of approximately 200 μV.

Published International Patent Application No. WO 00/054650 alsomentions non-invasive fECG and uterine contractions. It discloses anadaptive signal processing filter algorithm (ASPFA) which uses theuterine signal as a noise reference source together with the maternalECG to produce a fECG compensated for motion artefacts, attributed tothe uterine contractions, and maternal ECG artefact. A suggestion ismade that surface EMG signals can be used for the monitoring of uterinecontractions. Whilst emphasis is placed on the fact that no electrodelocations need to be specified, pairs of electrodes need to be locatedtogether and reference electrodes for the maternal ECG need to be placedaccordingly to aid the ASPFA. There appears to be no explanation of thenature of uterine electromyogram, its method of extraction and/or itsclinical significance.

Uterine activity monitoring using maternal abdominal electrodes todevelop EMG signals is disclosed in European patent application no.1,166,715 A2. Received EMG signals are filtered either with an analoguefilter or digitally in a microprocessor to monitor uterine activity.

The uterine contraction is said to be instigated at a site of pacemakercells located at the junction of the fallopian tube and the uterus.Effective contractions occur when what are referred to as bursts areproduced at this site. The bursts are most concentrated at the top ofthe uterus but spread across the uterus, at a rate of approximately 2 cmper second, with the climax of the contraction involving the whole ofthe uterus as described by Llewellyn Jones, “Fundamentals of Obstetricsand Gynaecology”.

As mentioned previously uterine activity occurs throughout pregnancywith action potentials occurring from a very early stage. Various typesof properties and waveforms have been attributed to electricalmyometrial activity as discussed by Devedeux et al, Am J Obstet Gynecol,1993, “Uterine Electromyography: A Critical Review”, these can bedescribed as (1) Slow Waves or (2) Fast Waves as follows. Slow Waves(1), tend to be associated with abdominal uterine measurements, ratherthan in vivo measurements, and are therefore assumed to be generated bymechanical artefacts such as skin stretching, their period typicallyequal to the contraction duration; (2) Fast Waves, Devedeux et al. haveseparated into a low frequency band (0.1-0.6 Hz) associated with uterinecontractions during pregnancy and parturition and a high frequency band(0.6-3 Hz) associated with progressive contractions during parturitiononly. Devedeux et al conclude that there are no fixed pacemaker sites:instead, like cardiac cells, myometrial cells can be excited by actionpotentials generated from a neighbouring cell (pacemaker follower cells)or generate their own impulses (pacemaker cells). Also suggested is thateach cell can alternate between these two functions. This appears toconflict with Llewellyn Jones, ‘Fundamentals of Obstetrics andGynaecology’ although this is concentrating on mechanical factors duringchildbirth which could be explained by an increased concentration ofpacemaker activity in the upper uterus during established labour.

Devedeux et al describe in vivo techniques, i.e. internal measurementsmade with electrodes attached to the uterus, and detected signals withan amplitude of 12-25 mV, although they conclude that these values aresignificantly reduced for abdominal recordings. They also conclude thatcontraction amplitude should not be used as a reference but moreemphasis placed on the spectral domain of the uterineElectrohysterogram: this makes it particularly advantageous to de-noisesignals efficiently whilst preserving frequency content.

Conventional monitoring of both fetus and mother during labour relies ontools such as Doppler ultrasound and cardiotocography (CTG), which lacksensitivity and specificity. CTG is a device which combinestocodynamometer and Doppler ultrasound to simultaneously monitorcontractions and heartrate respectively. The combination of these twomeasurements allows a measure of fetal well being to be formed based onheartrate accelerations and decelerations, particularly in response touterine contractions. The Dawes/Redman criterion is an example of ameasure of fetal well being used with CTG which looks for accelerations,decelerations, fetal movement, and heart rate variation under specifictime criteria. However in conditions such as Diabetes Mellitus thiscriterion is ineffective due to the absence of a high variation of heartrate. See Tincello D G, et al, ‘Computerised analysis of fetal heartrate recordings in patients with diabetes mellitus: the Dawes Redmancriteria may not be valid indicators of fetal well-being’, Journal ofPerinatal medicine. 1998; 26(2):102-6.

Diagnostic use of CTG appears to have limited effect on perinatalmortality or morbidity in high-risk pregnancies. The Cochrane databasesuggests there is a trend towards increased perinatal mortality (oddsratio 2.85, 95% confidence interval 0.99 to 7.12) in those assessed byCTG. Although the use of Doppler ultrasound in high-risk pregnanciesappears to improve a number of obstetric care outcomes and appearspromising in helping to reduce perinatal deaths, it has not been shownto be of benefit in low-risk populations. CTG is sometimes provided forambulatory monitoring of high risk groups at home although variablessuch as the tocodynamometer placement, application pressure, uterinewall pressure, subcutaneous fat limitations and data interpretation havea significant impact on its effectiveness. Dyson Donald C et al, 1998,“Monitoring Women at Risk for Preterm Labor”, New Eng Journal ofMedicine Volume 338:15-19, suggests women with home CTG monitoring haveno better outcome than women who have weekly visits by a nurse. Thissuggests that there may be a requirement for a device which provides aqualitative, non-invasive measurement of the occurrence, spectralcontent, and magnitude of uterine contractions.

It is an object of the invention to provide a device for non-invasivedetection of electrical muscular activity such as that arising fromuterine contractions.

The present invention provides a method of monitoring electricalmuscular activity non-invasively, the muscular activity being stationaryor non-stationary characterised in that the method incorporates thesteps of:

-   a) providing a signal separation technique suitable for separating    stationary signals,-   b) placing a plurality of low-noise signal electrodes externally    upon a patient's skin for detection of muscular activity, the    electrodes being localised sufficiently such that:    -   i) their muscular signal contributions simulate a single        muscular source to the signal separation technique despite any        non-stationarity of the muscular source, and    -   ii) the number of sources detected by the signal separation        technique is not more than the number of electrodes; and-   c) applying the signal separation technique to signals received from    the electrodes to separate the muscular source.

The invention provides the advantage that it makes it possible toseparate a muscular source using a signal separation technique suitablefor separating stationary signals despite the muscular activity beingnon-stationary, which compromises many such techniques as will bedescribed later.

The muscular activity may be uterine activity. The signal separationtechnique may be based on an instantaneous algorithm as hereinafterdefined, and may be independent component analysis (ICA). The step ofapplying the signal separation technique may apply ICA to processingdata derived from signals from the signal electrodes, the data beingarranged in successive overlapping blocks such that in pairs of adjacentblocks each subsequent block incorporates a proportion of the data inthe respective preceding block, and a correlation scheme is applied tore-order independent sources derived in ICA processing of differentblocks to correct for signal swapping.

The step of placing the signal electrodes may comprise placing four orfive signal electrodes at and above navel height with respect to anupright patient at positions close to the expected site of pacemakeractivity. The signal electrodes may be a first set of signal electrodesand the step of placing the signal electrodes may include placing asecond set of signal electrodes upon the patient's skin in positions notlocalised sufficiently for their muscular signal contributions tosimulate a single source to the signal separation technique, and thesignal separation technique then employs signals derived via the firstset of signal electrodes for monitoring non-stationary muscular activityand signals derived via the first and second sets of signal electrodesfor monitoring stationary muscular activity.

The signal separation technique may simultaneously acquire maternal andfetal cardiac activity, and also uterine activity, maternal muscleactivity, fetal ECG and maternal ECG. Frequency selective filtering maybe employed to facilitate separation of maternal and fetal cardiacactivity and uterine activity by limiting the scope for there being moresignals than sensors.

In another aspect, the invention provides an apparatus for monitoringelectrical muscular activity non-invasively, the muscular activity beingstationary or non-stationary, characterised in that the apparatusincorporates:

-   a) computer apparatus for implementing a signal separation technique    suitable for separating stationary signals,-   b) a plurality of low-noise signal electrodes placed externally upon    a patient's skin (40) for detection of muscular activity, the    electrodes being localised sufficiently such that:    -   i) their muscular signal contributions will simulate a single        muscular source to the signal separation technique despite any        non-stationarity of the muscular source, and    -   ii) the number of sources detected by the signal separation        technique will not be more than the number of electrodes; and-   c) processing means for processing signals received from the    electrodes into digital signals suitable for application of the    signal separation technique by the computer apparatus to separate    the muscular source.

The apparatus aspect of the invention may have preferred featuresequivalent mutatis mutandis to those of the method aspect.

Embodiments of the invention will now be described, by way of exampleonly, with reference to the accompanying drawings, in which:

FIG. 1 provides plots of uterine mechanical and electrical activityagainst time recorded with a tocodynamometer and apparatus of thisinvention respectively;

FIG. 2 shows a single burst of uterine electrical activity from FIG. 1on expanded horizontal and vertical scales;

FIG. 3 is a schematic illustration of an apparatus for simultaneouslyrecording uterine activity, fECGs and Maternal ECG in accordance withthe invention;

FIG. 4 is a schematic illustration of an abdominal electrodearrangement;

FIG. 5 is a flow diagram of a computer-implemented process to separateuterine and fECG signals from composite signals simultaneously;

FIG. 6 illustrates composite signals recorded using the electrodearrangement shown in FIG. 4;

FIG. 7 illustrates independent signal sources separated from compositesignals using the process of FIG. 5;

FIG. 8 is equivalent to FIG. 7 but corresponds to a reduced number oflocalised electrodes positioned to desensitise processing to signalnon-stationarity;

FIG. 9 schematically illustrates a visual display unit showing uterineelectrical activity alongside instantaneous heart rate and fECG;

FIG. 10 illustrates signal recording remotely from processing; and

FIG. 11 illustrates use of electrode-mounted buffer amplifiers.

With reference to FIGS. 1 and 2, a simultaneous recording of uterineelectrical activity using this invention and mechanical activity from atocodynamometer was made during a patient's labour and signal processingapplied to extract the electrical uterine activity. The mechanicalactivity is indicated generally by 20, and the electrical activity by atrain of pulses of electrical uterine burst activity such as 22 a, 22 band 22 c. The two forms of activity are shown plotted against a commontime axis. FIG. 2 shows individual action potentials within the singleburst 22 b of uterine electrical activity on expanded voltage and timescales.

Referring now to FIG. 3, an apparatus suitable for implementing thisinvention is indicated generally by 30. It comprises a number ofelectrodes 1, 2, 3, G and R suitable for placing on the surface of amother's skin and monitoring voltage signals developed there: here Gindicates a ground electrode, R a reference electrode and 1 to 3 aresignal electrodes. For convenience only five electrodes 1 etc. areshown, but in this example of the invention fourteen electrodes wereused as will be described later, G and R electrodes together with twelvesignal electrodes numbered 1 to 12 (4 to 12 not shown). The electrodes 1etc. are connected via respective screened leads 32 a to 32 e(collectively 32) to a lead box 34, which is also connected to acomputer 36.

The lead box 34 contains processing circuitry for signals from thesignal electrodes 1 etc. are shown inset at 34 a: circuitry is shown fortwo signal electrodes 1 and 2, dots D indicate like circuitry for othersignal electrodes. The circuitry comprises for each signal electrode 1etc. a respective low-noise differential amplifier 37 and a respectivehigh-pass and low-pass anti-aliasing filter 38. The filters 38 areconnected to a common multi-channel analogue to digital converter (ADC)39. The amplifiers 37 subtract a signal from the reference electrode Rfrom signals from respective signal electrodes 1 etc., and amplify theresulting difference signals. The difference signals are converted todigital signals by the ADC 39, and are then recorded and processed usingthe computer 36 to isolate the maternal uterine signal and the fECGsignal as will be described later in more detail.

A commercially available electroencephalography (EEG) system is suitablefor adaptation for acquisition and display of raw input composite data,i.e. signals from electrodes after processing at 30. Here the expressioncomposite refers to the fact that an electrode signal is a mixture ofsignals from different sources. The computer 36 is that from a portableEEG system (SYS98-Port24-CL) supplied by Micromed Electronics. UK Ltd.It is a battery-powered laptop computer running System '98 EEG recordingand analysis software (SYS-98) under Microsoft Windows NT operatingsystem. The SYS-98 software provides a convenient interface from the box34 to display apparatus (screen, not shown) and to a data storage medium(hard disk). To implement this example of the invention, special purposebespoke software has been developed and is also run on the computer 36:the bespoke software enables data recorded by EEG-specific software tobe read and processed to separate uterine activity and fetalcontributions. It also provides for display of parameters derived fromsuch activity and contributions (e.g. duration, intensity, frequencyspectrum for uterine activity and fetal heart-rate, PR, ORS, QTintervals for fECG). Operation of bespoke software will be described inmore detail later. The type of computer 36 is clearly not criticalhowever, all that is required is that it has sufficient processingcapacity for running the recording, processing and display software andsufficient memory for storing the recorded data, processed results andthe display itself. Preferably the computer should be portable. Not onlydoes this provide for ease of transfer to patients, but portablecomputers may be run on batteries in order to isolate them fromelectrical mains power supply and noise associated with that supply.

The lead box 34 and the computer 36, including a computer display screen(not shown) and recording and display software for raw composite data(as opposed to processed data which is specific to the presentinvention), as well as their connecting leads are all part of a portableEEG system.

The electrodes 1 etc. are commercially available, disposable,self-adhesive neurology electrodes (type 710 01-K) manufactured byNeuroline®. The principal preferences for the electrodes 1 etc. are thatthey are low-noise and of a type that is readily attached to a patientin such a way as to result in an impedance at the skin of less than 2kΩ. Moreover they must be sufficient in number to allow effective signalseparation by processing software. Each electrodes 1 etc. with itsrespective screened lead 32 contributes a respective single, separate,channel of data to a multichannel recording.

The 710 01-K electrodes sold commercially have a 10 cm length ofordinary (unscreened) cable attached to them. This type was selected asthe attached cable length is the shortest available. It is preferredthat this length of wire is nearer 1 cm, or that the electrodes areattached directly to the screened leads 32 as this would reduceelectrical noise further. Disposable electrodes with shorter cablespecific to fECG may be made to the same design.

The screened leads 32 are made from 0.9 mm coaxial screened cable of atype suitable for biomedical applications. They should be screenedsufficiently to reduce the noise level during fECG recordings to lessthan 3 μV. Connection is made to the lead box 34 by means of a D-typeconnector (not shown) having an outer metal case connected to ground forelectrical screening. The screened leads 32 connect the signalelectrodes 1 etc. to the lead box 34. An outer braided mesh layer of thecoaxial cable comprising each screened lead 32 is connected to isolatedground at the lead box 34 and to the metal case of the D-type connector.The earth electrode G is also connected to isolated ground at the leadbox 34. This provides a return bias current path to the mother's bodyfor common mode interference which will be rejected by amplifiers 38.

Eight or more signal electrodes 1 etc. are generally sufficient for fECGextraction to provide adequate abdominal coverage and to permit signalseparation into sufficient distinct sources. For example, using signalseparation as in GB4410, two or three apparently independent sources aregenerally detected for the maternal heart and typically one or two perfetus. The separation of artefact from uterine contractions is possiblefrom as few as three electrodes as there is a small number of sourcesand a narrow frequency band of interest. Additional electrodes allow theseparation of unwanted artefacts such as those associated with maternalbreathing, unwanted electrical interference, etc.

FIG. 4 is an illustration of one possible arrangement of electrodes 1etc. upon a mother's abdomen suitable for simultaneous monitoring ofuterine activity and fetal electrocardiogram (fECG). In this example,twelve signal electrodes 1 to 12, an earth electrode G and a commonreference electrode R are all attached to the external surface of amother's skin 40. Placement is indicated in the drawing by circlesindexed with reference numerals of corresponding electrodes. The commonreference electrode R and earth electrode G are attached adjacent to themother's navel N and the remainder are dispersed over substantially thewhole of the mother's abdominal area. With respect to the mother'sheight, electrodes 1 to 5 are below the navel N, electrodes 6 to 9 arelevel with it and electrodes 10 to 12 are placed above it midway betweenthe base of the sternum and the line of electrodes 6 to 9 that are levelwith the navel. Electrodes 10 to 12 are at a position which in latepregnancy and labour becomes substantially level with the top of theuterus or fundal height

Electrodes 1 to 12 are shown linked by network lines 42 indicating thatan approximately hexagonal arrangement of electrodes is convenientlyemployed for even abdominal coverage. This provides a regularly spacedarrangement of twelve abdominal electrodes with an electrode separationof about 10 cm. In this connection, it is recommended that for uterinemonitoring adjacent electrodes are separated by not more than 12 cm.This limit is set to cater for women with larger abdomens. It is notnecessary to stipulate a lower limit because the size of the abdomendictates this by limiting electrode deployment. In order to achieve gooduterine and fECG signal separation collectively, the signal electrodes 1to 12 should preferably not be placed too close together and shouldinvolve a wide coverage of the abdomen. A practical placement as shownin the drawing includes coverage from one side of the abdomen to theother and from the pubic hairline to the likely upper limit of theuterus. This latter can be judged from gestation or by following astandard configuration which is sufficient for the maximum height of theuterus which occurs late in pregnancy. It is a feature of this inventionthat because the electrodes 1 etc. are non-invasive, suitable placementcan readily be achieved by a midwife or trained lay person in the caseof smaller numbers of electrodes required for uterine activityacquisition.

All leads 32 should be kept as close as possible to the skin 40 and toeach other along their entire lengths, in order to reduce electrical andmagnetic noise through magnetic flux linkage of loops formed by thecombination of mother and leads. Each lead may incorporate a marker inthe form of a coloured band to indicate the 12 cm limit between adjacentelectrodes to facilitate rapid and accurate electrode placement.

In preparation for attachment and recording, ideally the mother will liecomfortably on a bed with the lead box 34 close by, but touching neitherthe patient nor the bed frame. She should be allowed to relax for a fewminutes to help reduce involuntary muscle activity. This is morenecessary for fECG purposes than for uterine monitoring, as the uterinefrequency band of interest is narrow relative to the fECG equivalent andis less susceptible to interference.

Voltage signals arising from uterine, cardiac, and other activity arepicked up by the signal electrodes 1 to 12, R attached to the skin 40.The signals pass to the lead box 34 via the screened leads 32. The leadbox 34 is referred to as a SAM 25R “headbox”, and is part of theMicromed Electronics EEG system. The advantage of an EEG headbox asopposed to an ECG lead box, is that the former has superior lower noiseelectronic circuitry and an increased number of input channels availablefor use. The input channels are configured for unipolar use.

Further specifications of the SAM 25R lead box of relevance to thisexample are: touch-proof safety connections, 4 KHz sampling, low-passanti-aliasing filter with cut-off frequency at 1 kHz, softwaredown-sampled to 512 Hz, pass band from 0.3-256 HZ and 12-bit resolutioncovering a voltage range of 2 mV.

The SAM 25R lead box 34 is a convenient and commercially availabledevice and was used for those reasons. However, in some respects it hasnon-ideal characteristics for the purposes of the invention. It has ahigh pass and low pass filter at its input and an amplifier with a noiselevel 0.16 μV, i.e. not as low as can be attained (<0.1 μV) whencompared with other EEG systems or through the design of a bespoke leadbox. The high pass filter might usefully be redesigned to rejectfrequencies less than 0.1 Hz instead of 0.3 Hz at present, and the lowpass filter to reject frequencies greater than ˜200 Hz, as opposed to 1kHz. This would reduce attenuation of low frequency uterine components,reject high frequency noise and improve anti-aliasing.

Detected source voltages range from 7 μV to 250 μV in the frequencyrange of 0.3 Hz-3 Hz, depending on the stage of pregnancy or labour.Intermittent spike activity (40 Hz-150 Hz) is also regularly observed:it will be separated from uterine activity and fECG with signalprocessing to be described. It is thought to be associated withabdominal musculature: no significant correlation has been found betweenintermittent spike activity and contractions other than that ofvoluntary contraction of the abdominal musculature and diaphragm whichmay be associated with the onset of a uterine contraction.

Multiple channel inputs to the lead box 34 are used in a unipolarconfiguration. That is, voltage readings are taken between eachabdominal electrode 1-12 and the common reference electrode R. Prior artfECG devices attempted to solve the problem of system noise by takingbipolar readings that attempt to cancel localised noise at the locationof the source.

Within the lead box 34, analogue voltage signals from each signalelectrode 1 to 12 are fed to one input of a respective differentialamplifier 37 and the voltage signal from the reference electrode R isfed to the other. Each differential amplifier 37 therefore outputs anamplified signal proportional to the difference between the voltagedeveloped at the associated signal electrode 1 to 12 and that developedat the reference electrode (R). The resulting amplified signals arefiltered by respective anti-aliasing low-pass filters 38 and digitisedby the simultaneous multi-channel A/D converter 39. The advantage ofusing a multi-channel A/D converter 39 is that simultaneous sampling canbe arranged on all channels from electrodes 1 to 12, which is adesirable feature for subsequent signal processing. These digitisedsignals are then passed to the computer 36 for signal processing.

It is to be noted that although a unipolar configuration has advantages,a bipolar configuration is by no means precluded. The latter may bereplicated simply by taking differences between digitised unipolarchannel outputs, if such a bipolar configuration is required.

In setting up equipment for making uterine activity and fECG recordingsit is important to reduce ambient and system noise to as low a level aspossible. The following procedure has been found to produce sufficientlylow-noise readings:

-   i). The mother's skin 40 is lightly excoriated using standard    abrasive preparation tape (e.g. “Skinprep”, manufactured by 3M) and    then cleaned with an alcohol- or water-based swab.-   ii). The electrodes 1 to 12, G and R are attached to the skin 40    with light finger pressure.-   iii). The electrodes 1 to 12, G and R are then connected to    corresponding screened leads 32.-   iv). The screened leads 32 are connected to the lead box 34 via the    D-type screened connector (not shown).-   v). The apparatus 30 is battery powered for isolation from the mains    supply.-   vi). Skin impedance at the electrodes 1 to 12, G and R are measured    and any electrode having a skin impedance greater than 2 kΩ is    reapplied.-   vii). Screened leads 32 are gathered together and maintained close    to the mother's skin 40 in order to minimise magnetic pickup.-   viii). The apparatus 30 is set to display real-time signals derived    from abdominal electrodes 1 to 12, i.e. it has a respective    recording channel associated with each electrode.-   ix). Possible sources of electrical interference (such as mains) are    disconnected if possible.-   x). The computer 36 may record composite raw data from the box 34    and save them to its hard disk for further analysis and processing,    and/or may continually process and display such data.

Referring now to FIG. 5 and also to FIGS. 3 and 4 once more, signalprocessing within the computer 36 is indicated generally by a flowdiagram of a software-implemented procedure 50. The computer 36receives, from the lead box 34, twelve separate digital signalsassociated with respective signal electrodes 1 to 12. The computer 36processes these digital signals in parallel via two processing threads.Two filters 52 and 54 implemented in software define a uterine threadand a cardiac thread respectively, and all twelve signals are filteredby both in parallel.

The uterine filter 52 isolates uterine activity and is a low-passinfinite impulse-response (IIR) Butterworth filter of 9 taps with a passband of 0 to 3 Hz, stop-band of 7 Hz with attenuation of 60 dB: it has a3 dB point of 3.5 Hz and a pass band ripple of 0.01 dB. It does not havehigh pass filtering, because it is necessary to preserve a low frequencycomponent of uterine activity. Filtering is implemented using a zerophase forward and reverse digital filtering technique of known kind.

For fECG signals, signal sampling should be at a frequency of least 512Hz, ten times greater than that required for uterine signals because thelatter have much lower frequency content. All signals from the box 34are sampled by the computer at the rate appropriate for fECG. Signalsfiltered by the uterine filter 52 are subsequently decimated at 56 by afactor of 10 (90% reduction in data) to an approximately 50 Hz samplingrate to reduce computation and improve signal separation by rejectingunwanted frequency bands. It is convenient to filter and decimate alltwelve signals at 52 because it allows selection of signals fromdifferent localised groups of electrodes for subsequent processing.

At 58, some of the signals are omitted to concentrate on signals fromselected electrodes and not others. In this example only five of thesesignals are retained in the uterine channel. The five retained signalsare those obtained from electrodes 7, 8, 10, 11, and 12 in FIG. 4 afterprocessing at 34. At 60, blind signal separation (BSS) is carried out(as will be described later) to separate signals (or sources) ofdifferent types. Subsequently, at 62, the separated signals areclassified as uterine or otherwise. The uterine source(s) may beextracted either manually or automatically from other separatedartefacts and reconstructed. It is subsequently parameterised at 64 toidentify key features relating to uterine activity and displayed at 66.

Similarly, the fECG filter 54 isolates fECG activity: it consists of ahigh-pass IIR filter of 6 filter taps, and a low-pass finiteimpulse-response (FIR) filter of 9 filter taps. The high-pass filter isdesigned using an IIR Butterworth filter with a passband of 2 Hz,stop-band of 0.1 Hz and stop-band attenuation of 120 dB, resulting in a3 dB point of 1 Hz and a passband ripple of 0.01 dB. The low-pass filteris designed using a Blackman window with a band-edge at 150 Hz.Filtering is implemented using a zero phase forward and reverse digitalfiltering technique. Digital signals filtered at 54 are processed at 68to separate signals of different types. Subsequently, at 70, theseparated signals are classified as fECG or maternal. Like the uterinesignal, the fECG signal is then parameterised at 64 to identify keyfeatures and displayed at 66. The uterine signal is displayed alongsidethe fECG signal.

Blind signal separation or BSS at 60 and 68 will now be described. Theexpression “blind” indicates that no assumptions are made about signalcharacteristics or processes which form signal mixtures. It does notrely on foreknowledge of signal characteristics such as arrivaldirection, frequency, waveform, timing, modulation etc. BSS onlyrequires signals to be statistically independent and for stationarityand linearity to prevail. Stationarity means that signals and theirmixing channels do not change with time. Linearity means that the signalmixtures are linear combinations of different signals.

In investigating the separation of uterine and fECG signals using theelectrode arrangement shown in FIG. 4, it was found that a well knownand popular form of BSS, independent component analysis (ICA), produceduseful fECG results but not sufficiently useful uterine results. Thiswas investigated as follows. The uterine signal of interest arises fromuterine contractions which are triggered by pacemaker cells which duringlabour are more concentrated in the upper uterus at the level ofelectrodes 10 to 12. A contraction propagates relatively slowly down theuterus at ˜2 cm/sec, so if a contraction was initiated from the top ofthe uterus it could take up to ˜12 sec to reach the level of thelowermost electrodes 1 and 2 in FIG. 4. It is therefore non-stationary.A version of ICA employed in this example (preferred for other reasons)is limited to stationary signals: signals from electrodes 1 and 12 forexample may provide undelayed and delayed versions of a uterine signalrespectively, and ICA treats the delayed signal as a different signal tothe undelayed signal instead of the same signal apart from relativedelay. Similarly a change in morphology of action potentials over thewhole myometrium due to different combinations of pacemaker andpacemaker follower cells may result in more sources than sensors, whichmeans ICA will not provide full signal separation.

It is important to use a BSS algorithm such as ICA which is not overlycomplex so that results can be obtained in real time during labour, orwith the shortest delay possible. Most ICA algorithms are addressed tothe simplest form of BSS problem referred to as the instantaneous mixingproblem: here the signals are assumed to arrive synchronously at eachsensor in the array.

Many different algorithms such as ICA are available for solving theinstantaneous mixing problem. Unfortunately, an algorithm which isadequate for the instantaneous mixing problem experiences theaforementioned consequences when faced with a more difficult problemwhich involves relative delay of mixed signals and expressedmathematically as a convolution. This “convolutive mixing” problem canbe dealt with as described in International Patent Application No. WO03/073612 A2, but the processing burden is high and that militatesagainst its use in a real time application.

An alternative and simpler approach to solving the uterine signal delayproblem was discovered. Being at the surface of the abdomen remote fromthe uterus, any electrode receives the uterine signal after apropagation time delay has elapsed from the associated contraction beinggenerated within the mother. It was found that good separation of theuterine signal was obtained by restricting its gathering to a localisedgroup of electrodes: this group was selected to have time delays forreceipt of the uterine signal which were sufficiently similar to providefor the signal separation process to treat their uterine contributionsas the same signal.

Additionally, using a localised group of electrodes limits the number ofuterine sources which may be due to pacemaker cells across the wholemyometrium changing the morphology of action potentials. Any grouping ofneighbouring electrodes in FIG. 4 will satisfy this. However, in trialsconducted to date, the strongest signals and best signal to noise ratioare obtainable from electrodes 7, 8, 10, 11 and 12 in FIG. 4 near/levelwith and above the navel N, because these electrodes are locatedrelatively close to and substantially equidistant from the position ofthe top of the uterus during labour where there is a concentration ofcells acting as pacemakers initiating uterine contractile waves. Theelectrodes 7, 8, 10, 11 and 12 therefore receive respective uterinecontraction signals without significant delay relative to one another,i.e. any relative delay is not sufficient to compromise results from aninstantaneous algorithm such as ICA. These electrodes also receiverespective uterine contraction signals from a local group of pacemakercells rather than several pacemaker sites across the myometrium. Thislocalised group of electrodes limits the effect of non-stationaryuterine signals making them simulate stationary signals and restrictsthe number of sources for the purposes of processing by an ICAalgorithm.

An alternative approach to minimising the number of sources due to theconvolutive nature of the data is to consider the frequency domainrather than the time domain as this allows time-delays to be modelledthrough the use of frequency bins. This has inherent problems because alarge number of frequencies must be considered together with apermutation/amplitude correction required for each. A simplifiedapproach is discussed by Dapena A. and Serviere C, ICA2001, ‘Asimplified frequency-domain approach for Blind Separation of Convolutivemixtures’. The main disadvantages of a frequency domain approach is thatit is highly computational, although it may prove to be a useful tool inanalysing the frequency content of non-stationary uterine activityacross the entire myometrium. ICA is a well known analytical technique:see e.g. “Independent Component Analysis—theory and applications” byT-W. Lee, published by Kluwer Academic, Boston (1998). The ICA algorithmused in this example is that disclosed by I. J. Clarke in “DirectExploitation of non-Gaussianity as a Discriminant”, EUSIPCO '98, Rhodes,Greece, 8-11 Sep. 1998. It has been found to be particularly effective.ICA has not previously been applied to extraction of uterine electricalactivity. Uterine electromyography has often been investigated using apair of abdominal electrodes, but ICA ideally requires at least as manysensors as sources, which leads to problems created by multiplepacemaker sites and non-stationary signals. Moreover, successfulseparation of biological signals by ICA with data recorded over severalminutes is difficult due to biological signal mixtures andelectromagnetic interference changing with time.

ICA requires data to be processed in blocks that are sufficiently longto ensure that signals are statistically independent. ICA has anambiguity in that it returns signals it has assigned to temporalindependent sources in an arbitrary order, as described by Z. Markowitzand H. Szu, “Blind Demixing Real-Time Algorithm of Piecewise TimeSeries”, Internal Joint Conference on Neural Networks IJCNN '99, pp.1033-1037, 1999. This is otherwise known as a permutation problem: itmakes processing data in blocks difficult because separated signals arereturned for a block in usually a different and unknown order comparedto those for an adjacent block. It can be referred to as signalswapping, and means that signals cannot be tracked from block to block.It is dealt with in this example by introducing prior data from eachdata block to a respective immediately following block. To overcome thesignal swapping problem, pairs of adjacent blocks X₁ and X₂, X₂ and X₃etc. are overlapped sufficiently so that e.g. X₂ contains samplescorrelated with those of X₁. A correlation scheme is then applied tore-order independent sources determined by ICA for each block to correctfor signal swapping. This assumes that no significant artefact isintroduced in X₂ which would alter a mixing matrix M generated in ICAand change independent sources so that the correlation scheme wouldfail. The likelihood of this occurring can be reduced by using anoverlap, for example, 50% of the block length, though the preciseoverlap is not critical and may be optimised by experiment. The resultis a continuous signal on a single channel for the signal of interest,i.e. not swapped between channels.

Consequently, to carry out ICA for the uterine signals, recorded datafrom 58 was segmented into successive smaller blocks of 500 samples(sample window). Each sample was a snapshot of data, i.e. it consistedof five simultaneously recorded signals, one such signal from each ofthe electrodes 7, 8, 10 to 12. Each data block was approximately 10 seclong with 50% overlap or redundancy; i.e. the first half of each blockwas the second half of its predecessor. Each block therefore shared itsfirst and second 250 samples with preceding and succeeding blocksrespectively. The blocks were processed individually by ICA in thecomputer 36. The incoming data stream first fills the 500-sample windowwith a block of data and the ICA algorithm calculates a de-mixing matrixin a known manner. The de-mixing matrix is then applied to incoming dataone sample (snapshot) from each sensor at a time as each sample streamsinto computer memory. In the mean time the window is updated on a ‘firstin first out’ basis with the next block of data, from which a newde-mixing matrix is calculated. The new updated mixing matrix wascalculated when 50% of the window length had been updated to allow thecorrelation scheme to be implemented. This technique relies on thede-mixing matrix remaining unchanged for at least the time it takes tocalculate the updated mixing matrix. The reduced window/block size of 10sec and 50% overlap proved effective although other values may be used.The above scheme is employed because the mixing matrix for the slidingwindow cannot currently be recalculated at the same rate as the samplinginterval updates it due to computational limitations. However, withimproved computation of the ICA algorithm, and further algorithm-basedschemes to address signal swapping, it will become possible to update anICA-derived de-mixing matrix in response to input of each sample or atleast in a non-critical time frame i.e. <1 second for uterinecontractions. This will remove the need to rely on the assumption thatthe de-mixing matrix remains unchanged until the new de-mixing matrix iscalculated. A technique which removes the need for this assumption isthe subject of patent application No. GB0236539.4 dated 14 Nov. 2003.

In what follows a particular example of the implementation of an ICAalgorithm is described that has been found to be advantageous, althoughit is not essential to use this particular technique. It is described inI. J. Clarke in “Direct Exploitation of non-Gaussianity as aDiscriminant”, EUSIPCO '98, Rhodes, Greece, 8-11 Sep. 1998. ICA will nowbe described in more detail. It is used at 60 to analyse signals fromfive electrodes 7, 8, 10, 11 and 12 for uterine monitoring and signalsfrom all twelve electrodes 1 to 12 for fECG monitoring. ICA defines aseparation method for observed composite data variables x_(i) (i=1 to n)based on the assumption that each is a linear or non-linear mixture ofsome unknown latent sources s_(j). The mixing process is also unknownand the sources are assumed to be statistically mutually independent andnon-Gaussian.

An index i is given by the electrode references 1 to 12 (FIG. 4)associated with the relevant data; i.e. electrode i gives rise to asignal which is processed by the lead box 34 and as shown in the flowdiagram 50 (up to but not including BSS) to provide a signal x_(i),where i=1 to n and n=5 (uterine) and n=12 (fetal) in this example. Eachsignal x_(i) was digitised at 34 and so comprises a number (say m) oftime samples of recorded data. The m time samples for signals associatedwith each of n electrodes collectively form an m×n data matrix X ofprocessed digital signals. From the data matrix X the ICA algorithmgenerates a mixing matrix M and a set of n independent sources s_(j)(j=1 to n) such that each sensor output x_(i) can be written as adifferent linear combination of s_(j) i.e.:

$\begin{matrix}{{\underset{\_}{x_{i}} = {\sum\limits_{j = 1}^{n}{m_{ij}\underset{\_}{s_{j}}\mspace{11mu}{or}}}},{{{as}\mspace{14mu}{matrices}\text{:}\mspace{11mu} X} = {SM}}} & (1)\end{matrix}$where X is a matrix whose columns are the n sets of processed electrodesignals x_(i) and S is an m×n matrix whose columns are the set of nindependent sources s_(j). A de-mixing matrix W is now defined which isthe inverse of the mixing matrix M, i.e. their product is the unitmatrix. In this way the composite data X is separated into differentindependent sources s_(j) of interest.

The demixing matrix W can be estimated in two stages, the generation ofan orthonormal basis e.g. using singular value decomposition (SVD), anda refinement to make them statistically independent. In the first stage,an SVD can be carried out on the (m×n) matrix X. SVD is a well-knowndecorrelation and normalising technique. The SVD of a matrix X can beexpressed as:X=UλV  (2)where U and V are orthonormal (m×m) and (n×n) matrices respectively andλ is an (m×n) diagonal matrix with positive real diagonal elements (thesingular values in SVD), arranged in decreasing order.

The columns of U are left orthonormal singular (temporal) vectors of Xand they contain information about sources s_(j). The rows of V areright orthonormal singular vectors of X and they contain informationabout the spatial distribution of the sources s_(j) (i.e. magnitude ateach sensor). The singular values λ are related to the power levelsassociated with individual temporal singular vectors.

In general, the estimated signals (contained in the columns of U) arenot fully separated. The reason for the failure of SVD to separate thesignals is that it constrains both the matrices U and V to be unitary.This is inherent in the SVD methodology as it is a second orderdecorrelation method, which is intended to remove all similaritiesbetween signal pairs in a set of signals. Mathematically, this meansthat decomposed vectors are made orthogonal. In many “real-life”signals, the spatial information (contained in the rows of V) of thesignals will be similar (correlated) and so a solution that makes themdissimilar will not succeed in separating them.

the source signals by a hidden rotation matrix. Determining this missingrotation matrix necessitates the use of higher order statistics (HOS).The use of HOS to separate unknown, independent signals is oftenreferred to as independent component analysis (ICA) and this is thesecond stage in the separation process.

The matrix X can be expressed as:X=URR ^(T) λV  (3)

Where R denotes an (m×m) rotation matrix and R^(T) its transpose. R isunitary, such that RR^(T) is equal to an identity matrix I. The rotationmatrix is determined using estimated signals contained in U.

In general, for q signals, where q≦m, R denotes a (q×q) matrix, Udenotes a (m×q) matrix, λ denotes a (q×q) matrix and V denotes a (q×n)matrix. In Equation (3), the estimated signals are contained in UR andestimated mixing is defined by R^(T)λV.

The separation process may treat the signal mixing process as acomplicated combination of rotation, stretching and shearing.Decorrelation removes the stretching and shearing effects, so that onlya rotation needs to be applied to separate the signals. Rotation cannotapply shearing or stretching, and thus cannot counteract decorrelation.

The method for the computation of R is described in the I. J. Clarkereference previously given, and other techniques are also known. Thismodel assumes that the sources s_(j) are point sources, which is clearlynot the case for physiological sources such as uterine action potentialswhich are of finite extent. It is a consequence of the ICA calculationin these circumstances that multiple, separated sources are apparentlyfound for the uterine activity with different morphology instead of amore convenient single source. If twelve abdominal sensors were to beused for uterine monitoring as shown in FIG. 4, from three to sevenapparent sources of uterine activity would be found by ICA, the numberdepending on factors such as electrode/source proximity, extent ofcontraction across the uterus and electrical conduction to the surface.The additional sources tend to be those associated with maternal ECG,fetal and electrode movement artefact and electromagnetic interference.While twelve electrodes are recommended for fECG separation, as has beensaid five may be used for uterine activity separation in this example.Using this number of electrodes reduces problems associated withnon-stationary uterine activity seen across the whole abdomen andreduces uterine activity to a single source; it allows additionalsources not representing uterine activity to consist of artefacts suchas maternal/fetal ECG, motion artefact and electromagnetic interference.

For the purposes of illustrating the problems which arise out of use ofnon-localised electrodes in monitoring uterine activity using ICA,twelve signals recorded over 30 minutes during a singleton (singlefetus) pregnancy during early labour using electrodes as shown FIG. 4:the signals were filtered at 52 in a frequency band from 0.3 to 4 Hzsuitable for extraction of uterine activity. A 130 second enlargement ofthese signals is shown in FIG. 6: the signals are numbered on the left 1to 12 to indicate the associated electrode in each case. In all twelvesignals approximately 45 seconds of uterine activity is visible inregions vertically below a curved bracket 80, although it is corruptedby a maternal ECG contribution; this contribution can be seen on signal10, where it is strongest and is identified by small spikes on lowfrequency action potentials of the uterine signals. It can also be seenon a number of other signals It is also corrupted by anothermuscle/movement artefact associated with labour shown in signal 12 whichoccurs beyond the uterine activity or contraction below 80. FIG. 6 showsthat information relating to uterine contraction may be difficult tointerpret because of mixing of signals of different types from differentsources.

Referring now to FIG. 7, ICA was applied to the signals 1 to 12 of FIG.6 and results are shown as separated sources S1 to S12 (marked on left):these sources are shown on a normalised vertical scale (not shown) sothat each source has unit power, and they are plotted against ahorizontal time axis (not shown). The form of the uterine signal is wellknown and shown in FIG. 2, which is compared with each of the separatedsources S1 to S12. Sources S2 to S6 inclusive, S8 and S9 all showstructure similar to FIG. 2 with relative delay increasing from S2 toS9: this shows that ICA indicates seven uterine sources are present(more conveniently there would only be one). As has been said this isattributed to non-stationarity of uterine activity. Also, actionpotentials may also be triggered simultaneously from different pacemakersites on the myometrium. This is a further mechanism for the creation ofmore uterine sources. Both of these effects are mitigated by the use ofa subset of the available electrodes 1 to 12 as described earlier.

S1, S10 and S11 are a maternal ECG and breathing artefact separated intoseparate sources: this artefact was visible on all of the signals 1 to12 shown in FIG. 6. ICA has separated into a single source S12 a largeartefact, which persisted beyond the duration of the uterine contractiongiving rise to the uterine signal. S12 contributed predominantly tosignal 12 in FIG. 6, but it also interfered with other such signals.

FIG. 8 illustrates the improvement obtained by restricting the localityof electrodes used for the uterine signal. It is equivalent to FIG. 7except that only four sources are shown. Although use of signals derivedfrom five signal electrodes was described earlier, in the case of FIG. 8only four such signals were used, these being derived via electrodes 7,8, 10 and 11 in FIG. 4. It should be added that any number of electrodescan be used in this regard so long as they are sufficiently localised.

Four sources are shown referenced on left SS1 to SS4. Comparison ofthese sources with FIG. 2 shows that uterine activity appears in SS1only. In other words uterine activity has been separated into a singlesource SS1 Without any artefact originally shown in FIG. 6. Source SS2has the periodicity of maternal heart rate and breathing, and so thematernal ECG and breathing artefact is also separated in the singlesource SS2. A remaining unidentified artefact results in two apparentsources SS3 and SS4: it is not associated with contractile activitybecause there is no similarity to SS1 or FIG. 2, and it extends beyondthe duration of uterine activity or contraction in SS1 which wasmonitored in parallel with a tocodynamometer for verification.

FIGS. 6, 7 and 8 demonstrate that it is straightforward to choose alocalised set of electrodes to which propagation delays for the uterinesignal are sufficiently similar for ICA to treat contributions to theuterine signal from these electrodes to be one signal. One can evenselect localised groups on trial and error basis and see how manyuterine signals are separated in ICA in each case. The criterion is thatICA should preferably separate only one uterine signal, althoughmultiple uterine sources may be selected and reconstructed at eachelectrode location with unwanted artefact removal.

In order to extract the uterine contraction from the separated sources,the output of each electrode can be reconstructed using only thecontribution from uterine activity. That is, each electrode trace isfirst modelled as a mixture of sources, and then reconstructed usingonly those sources of interest

${{\text{(}{x_{i}(m)}} = {\sum\limits_{j}{m_{ij}s_{j}}}},$j being restricted to the index associated with particular separatedsources). This gives rise to modified signals in which the uterineactivity is readily apparent and other sources have been suppressed.

In this embodiment of the invention, selection of the required sourcesis made manually and implemented using a source-selection icon displayedon the computer 36 next to each separated source. Each icon may betoggled between a “no” indicator, meaning discard the source and a “yes”indicator, meaning make use of it. This can be automated to displayuterine activity without operator intervention. Automation may use anadaptive threshold peak detection routine to detect action potentials ofuterine activity. It would adapt to the statistics of each separatedsource to maximise the likelihood of detecting envelopes of uterineactivity. Whilst monitoring during pregnancy this process may takeseveral minutes until a contractile source is found and until then allchannels would need to be monitored. Once a contractile source isidentified it may be monitored using this technique to allow each burstof contractile activity to be marked by a window for further analysis;such analysis may be spectral analysis to differentiate between twocategories of fast wave uterine activity referred to as Fast_(LOW) andFast_(HIGH), which can be used as indicators for onset of labour.

To extract fECG signals at 68 in FIG. 5, the procedure is as for uterineactivity monitoring except that signals derived from all twelve signalelectrodes 1 to 12 are used, i.e. across the whole of the patient'sabdomen. Compared to uterine signals, signal separation in fECG is notcomplicated by non-stationarity, because the fetal heart is small andconsequently the fetal electrocardiogram can be modelled as a pointsource surrounded by a homogeneous conduction medium. The fECG thereforehas stationarity for the purposes of ICA.

Although noise reduction is important in enabling uterine activity to beextracted readily throughout pregnancy from electrode signals, anapparently noisy signal may still prove useable. This is because the ICAtechnique will isolate separable noise for discarding. However,separable noise is not always distinguishable from inseparable noise inelectrode signals, and so it is important to reduce noise as far aspossible.

Abdominal surface intensity maps may be generated from separated sourcesby shading a map of geometrical locations of signal electrodes accordingto the strength of the coefficient m_(ij) ² of the desired source numberj (or combination of sources) at each signal electrode i. Brighter areasare used to Indicate higher levels of signal strength, this allows theposition of multiple uterine sources, which may have resulted from thenon-stationary uterine signal, to be identified at their respectivelocations across the abdomen. This may provide an insight intoprogressive and non-progressive contractions and also further analysisof propagation mechanisms across the myometrium.

It is not essential to carry out signal separation using ICA, but thistechnique and its I J Clarke version referred to above are preferred.Other signal separation algorithms are known, see for exampleInternational Patent Application No. WO 03/073612 A2 which reviews theprior art on instantaneous and convolutive mixing in addition toproviding a version of convolutive mixing. Standard band pass frequencyfiltering has been used in the prior art to view the uterine activityparticularly in labour when the signal is at its strongest. However, theICA/Clarke technique is preferred for detailed analysis of uterineactivity throughout pregnancy and during labour where there isconsiderable unwanted artefact. Substantial frequency filtering mayremove or degrade signals of interest due to overlapping frequencyranges of a desired signal and an artefact. In addition, waveletdenoising schemes have been used, as discussed previously, which (unlikeBSS) rely on prior knowledge of the interfering artefact.

Using prototype apparatus it has been found that it takes approximatelyfive minutes to apply a full array of signal electrodes 1 to 12 andground and reference electrodes G and R and begin monitoring. However,as described above, for acquisition of uterine activity fewer signalelectrodes are successfully employed, as few as three. Moreover,improvements to mathematical signal processing techniques and hardwaremay allow the number of electrodes to be reduced below eight for fECGacquisition, which involves a wider frequency spectrum and hence morepossible sources.

An electric guard potential may be applied to shielding of the screenedleads 32. It reduces the effects of lead capacitance and of mismatchbetween input capacitances. It increases the common mode noisecomponents of detected signals that are rejected by differentialamplifiers 37. Although the guard potential may be similar to the signalvoltage of interest, the shielding must be driven from a low impedancesource, such as for example a voltage follower driven by the signal ofinterest.

FIG. 9 schematically shows a display monitor 90 suitable for use indisplaying sources separated simultaneously as described above. Themonitor 90 shows separated electrical uterine activity 92, andinstantaneous heart rate 94 derived from an fECG 96. It is extremelyuseful to be able to monitor maternal and fetal parameters in this way,because during labour the fetus undergoes considerable stress.Monitoring the mother and fetus in real time or nearly so enables aclinician to intervene if stress increases dangerously. In the exampledescribed above results were obtained with a processing delay of ˜1 sec.

A variety of parameters may be set up at 64 in FIG. 5 for display andoutput on a monitor such as 90: e.g.:

-   i). Patient details for hospital records.-   ii). Raw, composite, multichannel abdominal input data (unipolar or    bipolar configuration).-   iii). Icon for manual or automatic selection of sources of interest    e.g. uterine, fetal, maternal.-   iv). Projection of data channels on to a subspace spanned by    selected sources to eliminate unwanted contributions.-   v). Positions of the uterine action potential peaks and bursts of    action potentials to be used as fiducial markers.-   vi). Frequency spectra of bursts of action potentials relating to    each contraction event by windowing contractile bursts.-   vii). Marking of fetal movement.-   viii). Uterine contractions against instantaneous fetal heartrate.-   ix). Uterine contractions against an fECG rhythm strip.-   x). Uterine activity in either electrical format or tocodynamometer    format.-   xi). Criteria, such as Dawes Redman, for fECG to indicate fetal    well-being and an alarm to indicate fetal compromise.-   xii). Patient record with parameters of interest such as uterine    contraction information, fECG rhythm strip and fetal heart rate.-   xiii). Database of patient data.-   xiv). Zoom facility to focus on fine detail, e.g. structure of    heart-beat, heart rate or waveform.-   xv). Parameters such as Heart rate variability, ST elevation and    other intervals that may be useful in diagnosing fetal well-being in    combination with uterine contractions.

Referring now to FIG. 10, a further embodiment 130 of the invention isshown: it is similar to the apparatus 30, and parts previously describedare like referenced with a prefix 100 but not described further. Itdiffers to the earlier embodiment 30 only in that in this embodiment 130a lead box 134 is connected to a transmitter indicated schematically byan antenna 149 a communicating with a corresponding receiver indicatedby 149 b and connected to a computer 136. The transmitter/receiver linkfrom the lead box 134 to the computer 136 enables the lead box 134 to beplaced close to or on the patient. Transmitting amplified data in thisway enables the screened leads 32 to be shorter than previously: theyonly need reach the nearby lead box 34. This further reduces scope fornoise pick-up and signal loss. In addition, the lack of long trailingleads and their physical connection to the computer 136 enables themother to be ambulatory, without leads or electrodes having to bedisconnected, potentially allowing her to relax more readily when arecording is to be taken.

Referring now to FIG. 11, a further embodiment 230 of the invention isshown: it is similar to the apparatus 30, and parts previously describedare like referenced with a prefix 200 but not described further. Eachelectrode 201 etc. is connected first to a respective pre-amplifier 231illustrated inset at 233, and each unit 231 is in turn connected to thelead box 234. Suitable pre-amplifiers are well known and will not bedescribed. The pre-amplifiers 231 are disposed adjacent respectiveelectrodes 201 etc. and provide a pre-processing stage. They amplifysignals propagating along leads 232, and the signals are thereforelarger and (compared to apparatus 30) relatively more immune to electricand magnetic noise sources to which the leads are exposed.

The invention may be used in other applications to monitor stationaryand non-stationary muscular activity in other organs, including those ofnon-human species. Smooth muscle lines the walls of other organs apartfrom the uterus including the intestine, arteries and veins, bladder,and secretary glands. Its primary role is to regulate the diameter ofthe organ lumen which it surrounds. Smooth muscle is characterised by aslow speed of contraction and ability to maintain contraction for longperiods at low energy cost. It can also be characterised by itsinnervation (nerve distribution) and propagation properties. The uterus,gut and bladder exhibit few areas of innervation and strong electricalcoupling through gap junctions. Therefore this invention may be used forexample to monitor bladder function by detecting and classifying anelectromyogram of the bladder. This would allow the bladder's detrusormuscle to be assessed for dysfunction, instability, absent orexaggerated reflexes and lack of co-ordination between itself and theurethral sphincter. This method may allow a preliminary non-invasiveurodynamic analysis of the patient or indeed provide a non-invasivefollow up to an invasive urodynamic test. The characterisation ofdetrusor and sphincter activity would be particularly useful in varioustypes of incontinence such as:

-   -   Nocturnal Enuresis, in the form of an audible patient warning to        wake the patient;    -   Urge Incontinence, to indicate the state of the detrusor and        predict involuntary contractions;    -   Overflow Incontinence, to provide a manual indication of the        bladder capacity through resting tone of the detrusor; and    -   Incontinence associated with pregnancy as an indication of        bladder capacity.

A similar technique could also be applied to the gut and lowerintestine.

1. A method for non-invasive monitoring of electrical muscular activitywhich is at least partially due to a non-stationary muscular source, themethod incorporating the steps of: a) providing a blind signalseparation technique suitable for separating stationary signals, b)placing a plurality of low-noise signal electrodes externally upon apatient's skin for detection of electrical muscular activity, the signalelectrodes being localised sufficiently such that: i) their muscularsignal contributions simulate a single muscular source to the blindsignal separation technique despite at least partial non-stationarity ofthe muscular source, and ii) the number of sources detected by the blindsignal separation technique is not more than the number of signalelectrodes; c) using computer apparatus to apply the blind signalseparation technique to digital signals derived from signals receivedfrom the signal electrodes to separate the muscular source, and d) usinga display device to display the separated muscular source to a user. 2.A method according to claim 1 wherein the muscular activity is uterineactivity.
 3. A method according to claim 1 wherein the blind signalseparation technique is based on an algorithm of a kind known as aninstantaneous algorithm and suitable for addressing blind signalseparation problems referred to as instantaneous mixing problems, theinstantaneous algorithm incorporating an assumption that signals arrivesynchronously at each sensor in a sensor array.
 4. A method according toclaim 3 wherein the instantaneous algorithm is independent componentanalysis (ICA).
 5. A method according to claim 4 wherein the step ofapplying the blind signal separation technique applies ICA to processingdata derived from signals from the signal electrodes, the data beingarranged in successive overlapping blocks such that in pairs of adjacentblocks each subsequent block incorporates a proportion of the data inthe respective preceding block, and a correlation scheme is applied tore-order independent sources derived in ICA processing of differentblocks to correct for signal swapping.
 6. A method according to claim 1wherein the step of placing the signal electrodes comprises placing fouror five signal electrodes at and above navel height with respect to anupright patient at positions close to the expected site of pacemakeractivity.
 7. A method according to claim 1 wherein the signal electrodesare a first set of signal electrodes and the step of placing the signalelectrodes includes placing a second set of signal electrodes upon apatient's skin in positions not localised sufficiently for theirmuscular signal contributions to simulate a single source to the blindsignal separation technique, and wherein the blind signal separationtechnique employs signals derived via the first set of signal electrodesfor monitoring non-stationary muscular activity and signals derived viathe first and second sets of signal electrodes for monitoring stationarymuscular activity.
 8. A method according to claim 7 wherein thenon-stationary muscular activity is uterine activity, the stationarymuscular activity is cardiac activity and the blind signal separationtechnique simultaneously acquires uterine activity and maternal andfetal cardiac activity.
 9. A method according to claim 8 wherein theblind signal separation technique acquires uterine activity, maternalmuscle activity, fetal ECG and maternal ECG.
 10. An apparatus fornon-invasively monitoring electrical muscular activity which is partlydue to a first muscular source which is non-stationary and partly due toa second muscular source which is stationary, characterised in that theapparatus incorporates: a) a first set of low-noise signal electrodesfor placing externally upon a patient's skin for detection of stationaryand non-stationary muscular activity, the first set of low-noise signalelectrodes being suitable for localisation sufficiently such that: i)their muscular signal contributions associated with the first muscularsource will simulate a single stationary source to a blind signalseparation technique despite the non-stationarity of the first muscularsource, and ii) the number of sources detected by the blind signalseparation technique will not be more than the number of signalelectrodes in the first set thereof; b) a second set of low-noise signalelectrodes for placing externally upon a patient's skin for detection ofstationary muscular activity; c) electronic signal processing circuitryfor processing signals received from the first and second sets oflow-noise signal electrodes into digital signals suitable forapplication of a computer-implemented blind signal separation technique;and d) computer apparatus programmed to implement a blind signalseparation technique suitable for separating stationary signals, and touse the technique to: i) process digital signals derived from signalsreceived from the first set of low-noise signal electrodes in order toseparate non-stationary activity associated with the first muscularsource, and ii) process digital signals derived from signals receivedfrom the first and second sets of low-noise signal electrodes in orderto separate stationary activity associated with the second muscularsource, and e) a display device for displaying the separated muscularsource to a user.
 11. An apparatus according to claim 10 wherein thenon-stationary first muscular source is a uterine source.
 12. Anapparatus according to claim 10 wherein the blind signal separationtechnique is based on an instantaneous algorithm.
 13. An apparatusaccording to claim 12 wherein the instantaneous algorithm is independentcomponent analysis (ICA).
 14. An apparatus according to claim 13 whereinthe computer apparatus is programmed to arrange the digital signals insuccessive overlapping data blocks such that in pairs of adjacent blockseach subsequent block incorporates a proportion of the data in therespective preceding block, and to apply a correlation scheme tore-order independent sources derived in ICA processing of differentblocks to correct for signal swapping.
 15. An apparatus according toclaim 10 wherein the first set of low-noise signal electrodes comprisefour or five signal electrodes for placing at and above navel heightwith respect to an upright patient at positions close to the expectedsite of pacemaker activity.
 16. An apparatus according to claim 10wherein the blind signal separation technique is arranged to employsignals derived via the first set of signal electrodes for monitoringuterine activity and signals derived via the first and second sets ofsignal electrodes for monitoring maternal and fetal cardiac activity.17. An apparatus according to claim 16 for monitoring uterine activitywherein the blind signal separation technique is arranged to acquirematernal and fetal cardiac activity simultaneously.
 18. An apparatusaccording to claim 16 wherein the blind signal separation technique isarranged to acquire uterine activity, maternal muscle activity, fetalECG and maternal ECG.
 19. An apparatus according to claim 10 wherein thecomputer apparatus is programmed to: a) apply a first filteringprocedure to digital signals derived from signals received from thefirst set of low-noise signal electrodes in order to derive uterineactivity, and b) apply a second filtering procedure to digital signalsderived from signals received from the first and second sets oflow-noise signal electrodes in order to derive cardiac activity.